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Senior data scientist

London
Data scientist
Posted: 7 January
Offer description

We have partnered with 1,500 companies to deliver a new kind of learning thats transforming today’s workforce. Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance. In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn. But we aren’t stopping there. With a strong operational footprint and 800 employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output. Join Multiverse and power our mission to equip the workforce to win in the AI era. As a Senior Data Scientist, you will play a pivotal role in steering our Data Science team towards achieving strategic objectives. Your expertise will guide collaborative efforts in product and backend services alike, whilst collaborating with product experts, engineers and other stakeholders from across the organization. Youll leverage your advanced analytical skills and understanding of AI and machine learning to drive impactful insights and foster innovative solutions. This dynamic role demands a balance of creativity and analytical rigor within a fast-paced environment, ensuring quick learning and iteration based on user feedback. What you’ll focus on: • Translate complex stakeholder queries and hypotheses into actionable analyses, experiments and AI/ML model requirements. • Develop a comprehensive understanding of our data lineage and sources, addressing and mitigating sampling and analytical biases. • Oversee the productionization of analyses and models, ensuring their seamless operation at scale by adhering to software engineering best practices. • Drive targeted exploration of our data landscape, ideating and implementing innovative ways to use data for enhancing user engagement on our products • Build out our knowledge graph capability for underpinning AI/ML models and agentic workflows • Proactively monitor and refine analyses and models, optimizing effectiveness and efficiency while minimizing biases and operational challenges. • Evaluate and validate scalable methodologies for data collection and processing, ensuring robust practices are in place. • Communicate actionable insights to stakeholders at all levels, bridging the gap between technical concepts and business objectives. What we’re looking for: Required: • 5 years of data science/machine learning experience, with a proven track record in leading complex data projects. • Extensive experience in deploying supervised/unsupervised machine learning algorithms and AI tools into production, delivering scalable and effective solutions. • Strong proficiency in Python and key libraries commonly used in machine learning (e.g., NumPy, Pandas, Scikit-Learn, PyTorch, Langchain). • Advanced working knowledge of SQL • Experience with GitHub for version control. • Demonstrated experience productionising ML models and analytic outputs within cloud environments (e.g., AWS, Azure). • Understanding of best practices in data protection and information security. • A tenacious, curious, and pragmatic approach to problem solving, focusing on creating usable, scalable outputs. • Exceptional attention to detail and a strong analytical mindset. • A growth-oriented attitude and a passion for continuous learning and professional development. • A commitment to Multiverse’s mission and values. Non-Required (But Desirable): • Familiarity with the education/skills sector • Understanding of the semantic web, knowledge graphs and/or network analytics • Direct experience with CI/CD practices (e.g., GitHub Actions). • Knowledge of infrastructure as code tools (e.g., Terraform). • An advanced degree in a numerical, engineering or related discipline. Benefits • Time off - 27 days holiday, plus 7 additional days off: 1 life event day, 2 volunteer days and 4 company-wide wellbeing days and 8 bank holidays per year • Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Gympass and access to Spill - all in one mental health support • Hybrid work offering - and the opportunity to take part in our work-from-anywhere scheme • Team fun - weekly socials, company wide events and office snacks

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